Exploring the Kaggle Hotel Booking Dataset: Insights and Trends for Better Hotel Bookings

Introducing a dataset of over 119,000 hotel bookings, researchers from Kaggle have created the perfect resource for travel industry professionals looking to better understand the behavior of their potential customers. With data collected from hotels in multiple locations, this dataset provides a remarkable insight into hotel bookings and guest behavior trends. In this blog post, we will dig deeper into the Kaggle Hotel Booking dataset and explore the most impactful insights offered by this data.

Understanding the Kaggle Hotel Booking Dataset

The Kaggle Hotel Booking dataset comprises booking information for two different hotels, one located in Lisbon and the other in Portugal. To be more precise, the dataset includes data from City Hotel and Resort Hotel and details such as booking date, arrival and departure date, number of guests, room type, and more. Crucially, the dataset also offers information about whether a reservation was canceled or not.

The Insights within the Dataset

As a travel industry expert, you’ll be well aware of the high cancellation rates that are typical of hotel bookings. However, the Kaggle dataset offers an intriguing insight into cancellations specifically: a considerably higher rate of cancellations for City Hotel as compared to Resort Hotel.

Furthermore, the data highlights that bookings made several months ahead of the stay, typically over six months away, were most likely to result in a cancellation. This insight alone can be beneficial for hotels to create targeted promotional offers to strengthen bookings made in advance.

Another crucial factor when it comes to cancelations is the length of the stay. Guests who booked longer stays had the highest cancellation rates. Therefore, hotels can focus on offering promotions or rewards to guests who stay for more extended periods to reduce cancellations.

Trends in the Kaggle Hotel Booking Dataset

After carefully analyzing the Kaggle Hotel Booking dataset, we can see several trends emerging that could benefit the travel industry. For example, the data highlights a surge in bookings in August, which could be due to the peak summer holidays in Europe. Hotels in popular tourist destinations could use this data to make strategic decisions and increase room rates in high season while offering value deals in off-seasons.

Another trend within the data that jumps out is the noticeable difference in booking behavior between domestic and non-domestic guests. Non-domestic guests tend to book accommodation with shorter notice than their domestic counterparts. This data provides essential information for hotels and booking providers that can adjust pricing strategies accordingly and offer last-minute deals to international tourists.

Conclusion

The Kaggle Hotel Booking dataset is a treasure trove of information for anyone working in the travel industry, including hotel managers, travel agents, and booking providers. By analyzing the data, users can gain valuable insights into the behavior of their potential and current customers. The information ranges from cancelation trends to booking behavior, allowing industry professionals to make data-driven decisions that could be used to increase bookings and ultimately revenue.